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- Toward a Data-Type-Based Real Time Geospatial Data Stream Management System
- The advent of sensory and communication technologies enables the generation and consumption of large volumes of streaming data. Many of these data streams are geo-referenced. Existing spatio-temporal databases and data stream management systems are not capable of handling real time queries on spatial extents. In this thesis, we investigated several fundamental research issues toward building a data-type-based real time geospatial data stream management system. The thesis makes contributions in the following areas: geo-stream data models, aggregation, window-based nearest neighbor operators, and query optimization strategies. The proposed geo-stream data model is based on second-order logic and multi-typed algebra. Both abstract and discrete data models are proposed and exemplified. I further propose two useful geo-stream operators, namely Region By and WNN, which abstract common aggregation and nearest neighbor queries as generalized data model constructs. Finally, I propose three query optimization algorithms based on spatial, temporal, and spatio-temporal constraints of geo-streams. I show the effectiveness of the data model through many query examples. The effectiveness and the efficiency of the algorithms are validated through extensive experiments on both synthetic and real data sets. This work established the fundamental building blocks toward a full-fledged geo-stream database management system and has potential impact in many applications such as hazard weather alerting and monitoring, traffic analysis, and environmental modeling.
- Towards Communicating Simple Sentence using Pictorial Representations
- Language can sometimes be an impediment in communication. Whether we are talking about people who speak different languages, students who are learning a new language, or people with language disorders, the understanding of linguistic representations in a given language requires a certain amount of knowledge that not everybody has. In this thesis, we propose "translation through pictures" as a means for conveying simple pieces of information across language barriers, and describe a system that can automatically generate pictorial representations for simple sentences. Comparative experiments conducted on visual and linguistic representations of information show that a considerable amount of understanding can be achieved through pictorial descriptions, with results within a comparable range of those obtained with current machine translation techniques. Moreover, a user study conducted around the pictorial translation system reveals that users found the system to generally produce correct word/image associations, and rate the system as interactive and intelligent.
- Urban surface characterization using LiDAR and aerial imagery.
- Many calamities in history like hurricanes, tornado and flooding are proof to the large scale impact they cause to the life and economy. Computer simulation and GIS helps in modeling a real world scenario, which assists in evacuation planning, damage assessment, assistance and reconstruction. For achieving computer simulation and modeling there is a need for accurate classification of ground objects. One of the most significant aspects of this research is that it achieves improved classification for regions within which light detection and ranging (LiDAR) has low spatial resolution. This thesis describes a method for accurate classification of bare ground, water body, roads, vegetation, and structures using LiDAR data and aerial Infrared imagery. The most basic step for any terrain modeling application is filtering which is classification of ground and non-ground points. We present an integrated systematic method that makes classification of terrain and non-terrain points effective. Our filtering method uses the geometric feature of the triangle meshes created from LiDAR samples and calculate the confidence for every point. Geometric homogenous blocks and confidence are derived from TIN model and gridded LiDAR samples. The results from two representations are used in a classifier to determine if the block belongs ground or otherwise. Another important step is detection of water body, which is based on the LiDAR sample density of the region. Objects like tress and bare ground are characterized by the geometric features present in the LiDAR and the color features in the infrared imagery. These features are fed into a SVM classifier which detects bare-ground in the given region. Similarly trees are extracted using another trained SVM classifier. Once we obtain bare-grounds and trees, roads are extracted by removing the bare grounds. Structures are identified by the properties of non-ground segments. Experiments were conducted using LiDAR samples and Infrared imagery from the city of New Orleans. We evaluated the influence of different parameters to the classification. Water bodies were extracted successfully using density measures. Experiments showed that fusion of geometric properties and confidence levels resulted into efficient classification of ground and non-ground regions. Classification of vegetation using SVM was promising and effective using the features like height variation, HSV, angle etc. It is demonstrated that our methods successfully classified the region by using LiDAR data in a complex urban area with high-rise buildings.
- User Modeling Tools for Virtual Architecture
- As the use of virtual environments (VEs) is becoming more widespread, user needs are becoming a more significant part in those environments. In order to adapt to the needs of the user, a system should be able to infer user interests and goals. I developed an architecture for user modeling to understand users' interests in a VE by monitoring their actions. In this paper, I discussed the architecture and the virtual environment that was created to test it. This architecture employs sensors to keep track of all the users' actions, data structures that can store a record of significant events that have occurred in the environment, and a rule base. The rule base continually monitors the data collected from the sensors, world state, and event history in order to update the user goal inferences. These inferences can then be used to modify the flow of events within a VE.
- Using Reinforcement Learning in Partial Order Plan Space
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Partial order planning is an important approach that solves planning problems without completely specifying the orderings between the actions in the plan. This property provides greater flexibility in executing plans; hence making the partial order planners a preferred choice over other planning methodologies. However, in order to find partially ordered plans, partial order planners perform a search in plan space rather than in space of world states and an uninformed search in plan space leads to poor efficiency. In this thesis, I discuss applying a reinforcement learning method, called First-visit Monte Carlo method, to partial order planning in order to design agents which do not need any training data or heuristics but are still able to make informed decisions in plan space based on experience. Communicating effectively with the agent is crucial in reinforcement learning. I address how this task was accomplished in plan space and the results from an evaluation of a blocks world test bed.
- Visualization of Surfaces and 3D Vector Fields
- Visualization of trivariate functions and vector fields with three components in scientific computation is still a hard problem in compute graphic area. People build their own visualization packages for their special purposes. And there exist some general-purpose packages (MatLab, Vis5D), but they all require extensive user experience on setting all the parameters in order to generate images. We present a simple package to produce simplified but productive images of 3-D vector fields. We used this method to render the magnetic field and current as solutions of the Ginzburg-Landau equations on a 3-D domain.
- Voting Operating System (VOS)
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The electronic voting machine (EVM) plays a very important role in a country where government officials are elected into office. Throughout the world, a specific operating system that tends to the specific requirement of the EVM does not exist. Existing EVM technology depends upon the various operating systems currently available, thus ignoring the basic needs of the system. There is a compromise over the basic requirements in order to develop the systems on the basis on an already available operating system, thus having a lot of scope for error. It is necessary to know the specific details of the particular device for which the operating system is being developed. In this document, I evaluate existing EVMs and identify flaws and shortcomings. I propose a solution for a new operating system that meets the specific requirements of the EVM, calling it Voting Operating System (VOS, pronounced 'voice'). The identification technique can be simplified by using the fingerprint technology that determines the identity of a person based on two fingerprints. I also discuss the various parts of the operating system that have to be implemented that can tend to all the basic requirements of an EVM, including implementation of the memory manager, process manager and file system of the proposed operating system.
- Web-based airline ticket booking system.
- Online airline ticket booking system is one of the essential applications of E-commerce. With the development of Internet and security technology, more and more people begin to consume online, which is more convenient and personal than traditional way. The goal of this system is to make people purchase airline tickets easily. The system is written in JAVATM. Chapter 1 will introduce some basic conception of the technologies have been used in this system. Chapter 2 shows how the database and the system are designed. Chapter 3 shows the logic of the Web site. In Chapter 4 the interface of the system will be given. Chapter 5 tells the platform of this system.
- Web Services for Libraries
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Library information systems use different software applications and automated systems to gain access to distributed information. Rapid application development, changes made to existing software applications and development of new software on different platforms can make it difficult for library information systems to interoperate. Web services are used to offer better information access and retrieval solutions and hence make it more cost effective for libraries. This research focuses on how web services are implemented with the standard protocols like SOAP, WSDL and UDDI using different programming languages and platforms to achieve interoperability for libraries. It also shows how libraries can make use of this new technology. Since web services built on different platforms can interact with each other, libraries can access information with more efficiency and flexibility.
- A Wireless Traffic Surveillance System Using Video Analytics
- Video surveillance systems have been commonly used in transportation systems to support traffic monitoring, speed estimation, and incident detection. However, there are several challenges in developing and deploying such systems, including high development and maintenance costs, bandwidth bottleneck for long range link, and lack of advanced analytics. In this thesis, I leverage current wireless, video camera, and analytics technologies, and present a wireless traffic monitoring system. I first present an overview of the system. Then I describe the site investigation and several test links with different hardware/software configurations to demonstrate the effectiveness of the system. The system development process was documented to provide guidelines for future development. Furthermore, I propose a novel speed-estimation analytics algorithm that takes into consideration roads with slope angles. I prove the correctness of the algorithm theoretically, and validate the effectiveness of the algorithm experimentally. The experimental results on both synthetic and real dataset show that the algorithm is more accurate than the baseline algorithm 80% of the time. On average the accuracy improvement of speed estimation is over 3.7% even for very small slope angles.
- XML-Based Agent Scripts and Inference Mechanisms
- Natural language understanding has been a persistent challenge to researchers in various computer science fields, in a number of applications ranging from user support systems to entertainment and online teaching. A long term goal of the Artificial Intelligence field is to implement mechanisms that enable computers to emulate human dialogue. The recently developed ALICEbots, virtual agents with underlying AIML scripts, by A.L.I.C.E. foundation, use AIML scripts - a subset of XML - as the underlying pattern database for question answering. Their goal is to enable pattern-based, stimulus-response knowledge content to be served, received and processed over the Web, or offline, in the manner similar to HTML and XML. In this thesis, we describe a system that converts the AIML scripts to Prolog clauses and reuses them as part of a knowledge processor. The inference mechanism developed in this thesis is able to successfully match the input pattern with our clauses database even if words are missing. We also emulate the pattern deduction algorithm of the original logic deduction mechanism. Our rules, compatible with Semantic Web standards, bring structure to the meaningful content of Web pages and support interactive content retrieval using natural language.